cff-version: 1.2.0
abstract: "<p>This dataset supports the doctoral research of Rongxin Song, M.Sc., at Delft University of Technology (2021–2025), focusing on enhancing maritime situational awareness, collision avoidance, and human-MASS (Maritime Autonomous Surface Ships) interaction. It includes AIS (Automatic Identification System) data from the Rotterdam area (spanning 51.897°–51.913° N, 4.411°–4.425° E and 51.833°–52.167° N, 3.167°–4° E) collected between 1 and 15 October 2023. The dataset also contains Python scripts for DWA-based path planning and trajectory prediction, MATLAB scripts for modelling and visualizing trust dynamics, and supporting files in .csv, .png, .py, and .m formats. The research integrates ontology-driven knowledge maps, machine learning for preference-aware ship navigation, and trust behaviour analysis to address challenges in mixed waterborne transport system. This dataset provides a structured resource for replicating experiments in dynamic maritime environments, with a README file included for usage guidance.</p>"
authors:
  - family-names: Song
    given-names: Rongxin
    orcid: "https://orcid.org/0000-0002-9685-1605"
title: "Data and code underlying chapters 3-5 of the PhD thesis: Human-MASS Interaction in Decision-Making for Safety and Efficiency in Mixed Waterborne Transport Systems"
keywords:
version: 1
identifiers:
  - type: doi
    value: 10.4121/2311d80d-fb88-420d-bd66-4019207fdb5d.v1
license: CC BY-NC-SA 4.0
date-released: 2025-01-15